{"id":"W2163360744","doi":"10.1109/mwsym.1995.405992","title":"Analytic Johns matrix and its applications in TLM diakoptics","year":2002,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Technical University of Nova Scotia","funders":"","keywords":"Dimension (graph theory); Matrix (chemical analysis); Convolution (computer science); Computation; Computer science; Domain (mathematical analysis); Algorithm; Matrix algebra; Algebra over a field; Applied mathematics; Mathematics; Combinatorics; Pure mathematics; Artificial intelligence; Mathematical analysis; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004209665,0.000371933,0.000240849,0.0009246731,0.0004402175,0.0007449829,0.000443958,0.0004487087,0.004624531],"category_scores_gemma":[0.00205099,0.000187728,0.0002289437,0.0008136573,0.000748571,0.0009231613,0.000774878,0.0006436454,0.001067287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004653904,"about_ca_system_score_gemma":0.0004438727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006713251,"about_ca_topic_score_gemma":0.0009957179,"domain_scores_codex":[0.9998226,0.00004991064,0.000008762199,0.00001745809,0.00008645903,0.00001492907],"domain_scores_gemma":[0.9996517,0.0001584419,0.000038789,0.00004916674,0.00007443799,0.00002755559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000477059,0.00002896151,0.0003656168,0.0001069226,0.000006339252,0.0002946604,0.0001668355,0.05635525,0.01033948,0.858636,0.002943339,0.07070877],"study_design_scores_gemma":[0.000008455186,0.00002939434,0.0002728042,0.00002254121,0.000004341888,0.0003672039,0.00006530731,0.715745,0.005789389,0.263377,0.01429854,0.00002000021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01796035,0.0006912425,0.9544885,0.0004181188,0.000145843,0.00003388755,0.00006203325,0.0004888842,0.02571117],"genre_scores_gemma":[0.487702,0.001615844,0.4891843,0.0002251442,0.0002502306,0.0001035016,0.0001332228,0.0003252672,0.02046042],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004624531,"threshold_uncertainty_score":0.01547056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01713141888344625,"score_gpt":0.2724279221235925,"score_spread":0.2552965032401462,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}